Highly-motivated employee with desire to take on new challenges. Strong worth ethic, adaptability and exceptional interpersonal skills. Adept at working effectively unsupervised and quickly mastering new skills.
Constructed a supervised machine learning model, Employing logistic regression to classify individual earnings based on specific features, including geographical location, education qualification, race, sex, and marital status. The model exhibited a robust performance, achieving an AUC-ROC of over 85% and an accuracy of 91%. Designed and implemented a robust database and ETL pipeline, Using AWS DynamoDB and Lambda functions. This system was dedicated to detecting faults in industrial machinery, offering real-time insights. Data was stored efficiently in DynamoDB, ensuring seamless fault monitoring and analysis. Spearheaded the development of a comprehensive Inventory database, For the assembly shop. Leveraged expertise in VBA, Macros, and SQL Queries, in conjunction with Microsoft Access, to optimize inventory management. This system enhanced efficiency and inventory control on a multinational scale.